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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Pinelli, F. Di Lorenzo, G. Calabrese, F. |
| Copyright Year | 2015 |
| Description | Author affiliation: IBM Res., Dublin, Ireland (Pinelli, F.; Di Lorenzo, G.; Calabrese, F.) |
| Abstract | In this paper we address the use of mobile phone location data to build urban sensing applications. In the past decade, several research works have proposed the use of different types of location data from the telecommunication network to characterise people mobility in the city. Thus, several applications to infer urban dynamics where proposed. However, different papers have used different types of mobile phone location data, making it is difficult to understand whether a particular dataset provided by a telecom operator is indeed effective for a specific urban sensing application. In this paper we address this issue by comparing the quality of the insights extracted from different types of mobile phone location data, with specific reference to two urban sensing applications: people count by location, and people flow between locations. Experiments executed on a real dataset provided by a telecom operator in Belgium show the advantages of using network-driven mobile phone location data (collected regardless on whether people are using their phone) compared to the widely used Call Detail Records. |
| Starting Page | 219 |
| Ending Page | 226 |
| File Size | 5164082 |
| Page Count | 8 |
| File Format | |
| e-ISBN | 9781479999729 |
| DOI | 10.1109/MDM.2015.33 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-06-15 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Mobile handsets Sensors Internet Telecommunications Data mining Estimation |
| Content Type | Text |
| Resource Type | Article |
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